Abstract

Pervasive computing requires infrastructures that adapt to
changes in user behaviour while minimising user interactions. Policy-
based approaches provide adaptability but, at present, require policy
rules to be provided by users. This paper presents preliminary work on
using Inductive Logic Programming (ILP) to automatically acquire such
knowledge from observational data. We show how a non-monotonic ILP
system called XHAIL can incrementally learn and revise rules of user
behaviour and we brie
y discuss how this approach might be exploited
within a wider pervasive computing framework.